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The purpose of this paper is to compare the use of two Object-Relational models against the use of a post-Relational model for a realistic application. Although real-world applications, in most cases, can be adequately modeled by the Entity-Relationship (ER) model, the transformation to the popular Relational model alters the representation of structures common in reality, like multi-valued and composite fields. Alternative database models have been developed to overcome these shortcomings.

Based on the ER model of a medical application, this paper compares the information representation, manipulation and enforcement of integrity constraints through PostgreSQL and Oracle, against the use of a post-Relational model composed of the Conceptual Universal Database Language (CUDL) and the Conceptual Universal Database Language Abstraction Level (CAL).

The CAL/CUDL pair, although more periphrastic for data definition, is simpler for data insertions, does not require the use of procedural code for data updates, produces clearer output for retrieval of attributes, can accomplish retrieval of rows based on conditions that address composite data with declarative statements and supports data validation for relationships between composite data without the need for procedural code.

To verify, in practice, the conclusions of the paper, complete implementation of a CAL/CUDL system is needed.

The use of the CAL/CUDL pair would advance the productivity of database application development.

This paper highlights the properties of realistic database-applications modelling and management that are desirable by developers and shows that these properties are better satisfied by the CAL/CUDL pair.

The relational model and relational database management systems have been the de facto industry standard for organizing and managing data in most computer‐integrated manufacturing environments. In recent years, however, some new database technologies have emerged – namely, object‐oriented and hybrid or extended relational – making the job of the CIM managers more difficult with regard to selecting a database technology that would be most appropriate for their operations. Presents a framework for selecting an appropriate DBMS type in a CIM setting depending on a company′s ENTITY and DATA needs. It is hoped that the presented framework would prove useful to practising managers.

Enterprise knowledge graphs (EKG) in resource description framework (RDF) consolidate and semantically integrate heterogeneous data sources into a comprehensive dataspace. However, to make an external relational data source accessible through an EKG, an RDF view of the underlying relational database, called an RDB2RDF view, must be created. The RDB2RDF view should be materialized in situations where live access to the data source is not possible, or the data source imposes restrictions on the type of query forms and the number of results. In this case, a mechanism for maintaining the materialized view data up-to-date is also required. The purpose of this paper is to address the problem of the efficient maintenance of externally materialized RDB2RDF views.

This paper proposes a formal framework for the incremental maintenance of externally materialized RDB2RDF views, in which the server computes and publishes changesets, indicating the difference between the two states of the view. The EKG system can then download the changesets and synchronize the externally materialized view. The changesets are computed based solely on the update and the source database state and require no access to the content of the view.

The central result of this paper shows that changesets computed according to the formal framework correctly maintain the externally materialized RDB2RDF view. The experiments indicate that the proposed strategy supports live synchronization of large RDB2RDF views and that the time taken to compute the changesets with the proposed approach was almost three orders of magnitude smaller than partial rematerialization and three orders of magnitude smaller than full rematerialization.

The main idea that differentiates the proposed approach from previous work on incremental view maintenance is to explore the object-preserving property of typical RDB2RDF views so that the solution can deal with views with duplicates. The algorithms for the incremental maintenance of relational views with duplicates published in the literature require querying the materialized view data to precisely compute the changesets. By contrast, the approach proposed in this paper requires no access to view data. This is important when the view is maintained externally, because accessing a remote data source may be too slow.

The purpose of this paper is to introduce an expressive query language, called relational XML query language (RXQL), capable of dealing with heterogeneous Extensible Markup Language (XML) documents in data‐centric applications. In RXQL, data harmonization (i.e. the removal of heterogeneous factors from XML data) is integrated with typical data‐centric features (e.g. grouping, ordering, and aggregation).

RXQL is based on the XML relation representation, developed in the authors' previous work. This is a novel approach to unambiguously represent semistructured data relationally, which makes it possible in RXQL to manipulate XML data in a tuple‐oriented way, while XML data are typically manipulated in a path‐oriented way.

The user is able to describe the result of an RXQL query straightforwardly based on non‐XML syntax. The analysis of this description, through the mechanism developed in this paper, affords the automatic construction of the query result. This feature increases significantly the declarativeness of RXQL compared to the path‐oriented XML languages where the user needs to control the construction of the result extensively.

The authors' formal specification of the construction of the query result can be considered as an abstract implementation of RXQL.

RXQL is a declarative query language capable of integrating data harmonization seamlessly with other data‐centric features in the manipulation of heterogeneous XML data. So far, these kinds of XML query languages have been missing. Obviously, the expressive power of RXQL can be achieved by computationally complete XML languages, such as XQuery. However, these are not actual query languages, and the query formulation in them usually presupposes programming skills that are beyond the ordinary end‐user.

The purpose of this paper is to reduce the number of join operations for retrieving Extensible Markup Language (XML) data from a relational database.

The paper proposes a new approach to eliminate the join operations for parent‐child traversing and/or sibling searching such that the performance of query processing could be improved. The rationale behind the design of the proposed approach is to distribute the structural information into relational databases.

The paper finds that the number of join operations which are needed for processing parent‐child traversal and sibling search can be bounded under the proposed approach. It also verifies the capability of the proposed approach by a series of experiments based on the XMark benchmark, for which it has encouraging results.

Compared with previous approaches based on the structure encoding method, the proposed approach needs more space to store additional immediate predecessor's IDs. However, the approach has similar performance to others and it is much easier to implement.

The experimental results show that the performance of the proposed approach is less than 3 per cent of the well‐known MonetDB approach for processing benchmark queries. Moreover, its bulkloading time is much less than that for the MonetDB. There is no doubt that the approach is efficient for accessing XML data with acceptable overheads.

This paper contributes to the implementations of XML database systems.

Data protection requirements heavily increased due to the rising awareness of data security, legal requirements and technological developments. Today, NoSQL databases are increasingly used in security-critical domains. Current survey works on databases and data security only consider authorization and access control in a very general way and do not regard most of today’s sophisticated requirements. Accordingly, the purpose of this paper is to discuss authorization and access control for relational and NoSQL database models in detail with respect to requirements and current state of the art.

This paper follows a systematic literature review approach to study authorization and access control for different database models. Starting with a research on survey works on authorization and access control in databases, the study continues with the identification and definition of advanced authorization and access control requirements, which are generally applicable to any database model. This paper then discusses and compares current database models based on these requirements.

As no survey works consider requirements for authorization and access control in different database models so far, the authors define their requirements. Furthermore, the authors discuss the current state of the art for the relational, key-value, column-oriented, document-based and graph database models in comparison to the defined requirements.

This paper focuses on authorization and access control for various database models, not concrete products. This paper identifies today’s sophisticated – yet general – requirements from the literature and compares them with research results and access control features of current products for the relational and NoSQL database models.

Relatively little microcomputer software has been designed specifically for the storage and retrieval of bibliographic data. Information retrieval packages for mainframes and minicomputers have been scaled down to run on microcomputers, however, these programs are expensive, unwieldy, and inflexible. For this reason, microcomputer database management systems (DBMS) are often used as an alternative. In this article, criteria for evaluating DBMS used for the storage and retrieval of bibliographic data are discussed. Two popular types of microcomputer DBMS, file management systems and relational database management systems, are evaluated with respect to these criteria. File management systems are appropriate when a relatively small number of simple records are to be stored, and retrieval time for multi‐valued data items is not a critical factor. Relational database management systems are indicated when large numbers of complex records are to be stored, and retrieval time for multi‐valued data items is critical. However, successful use of relational database management systems often requires programming skills.

Getting the right information at the right time is one of the success factors of product development. However, there exist a great variety of data formats which make the bi‐directional data interchange among various development groups inefficient and costly. Due to the lack of adequate product and engineering data, design practitioners may find it difficult to transform the customer’s requirements to a value‐added product. This paper attempts to propose a hybrid database approach (HDA) to support effective data exchange among a case based reasoning knowledge repository and a corporate relational database model, presenting an integrated view of a company’s knowledge sources so as to enable better decision‐making by providing immediate access to key business information. To introduce machine learning capability to the whole system, case based reasoning (CBR) is embraced to capture past experience and knowledge for case matching in terms of product development issues. The significance of this research is the provision of a cross‐platform data exchange system, which is able to facilitate the creation of a conducive product development environment.

Grey relational analysis (GRA) proposed by Deng Julong is very useful to analyze medical data. The essential thought of GRA is to find a grey relational order, which can be used to describe the relation between the related factors based on data series. The two‐grade difference is a traditional method of GRA and the three‐grade difference is an improved one. The basic steps and formulae of GRA are introduced and GRA is used to analyze the experiment medical data, clinical trial data, data of clinical study and ambulatory and grouping medical data.

The “collaboratory” concept has recently entered the vernacular of the scientific community to reflect new modes of scientific communication, cooperation and collaboration made possible by information technology. The collaboratory represents a scientific research center “without walls” for accessing and sharing data, information, instrumentation and computational resources. The principal applications of the collaboratory concept have been in the physical and biological sciences, including space physics, oceanography and molecular biology. Discusses the attributes of the collaboratory, and applies the concept developed by computer and physical scientists to the design and operation of the SIPPACCESS prototype information system for complex data to be used through the Internet by sociologists, demographers and economists. Examines obstacles to collaboratory development for the social sciences. Concludes that four major obstacles will inhibit the development of collaboratories in the social sciences.